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Digital Dysmorphology Project

2016-01-12 12:38:23 | BioPortfolio

Summary

In this study, the investigators propose a novel method to detect Down syndrome using photography for facial dysmorphology, a tool called computer-aided diagnosis (CAD). After validating the method, this technology will be expanded to perform similar functions to assist in the detection of other dysmorphic syndromes.

By using photography and image analysis this automated assessment tool would have the potential to improve the diagnosis rate and allow for remote, non-invasive diagnostic evaluation for dysmorphologists in a timely manner.

Description

In this study, investigators propose a novel method to detect Down syndrome using photography for facial dysmorphology, a tool called computer-aided diagnosis (CAD) . Local texture features based on Contourlet transform and local binary pattern are investigated to represent the facial characteristics. A support vector machine classifier is then used to discriminate between normal and abnormal cases. Accuracy, precision and recall are used to evaluate the method. After validating the method, this technology will then be expanded to perform similar functions to assist in the detection of other dysmorphic syndromes.

By using photography and image analysis this automated assessment tool would have the potential to improve the diagnosis rate and allow for remote, non-invasive diagnostic evaluation for dysmorphologists in a timely manner.

Study Design

Allocation: Non-Randomized, Intervention Model: Parallel Assignment, Masking: Open Label, Primary Purpose: Health Services Research

Conditions

Down Syndrome

Intervention

photographs

Location

Children's National
Washington
District of Columbia
United States
20010

Status

Recruiting

Source

Children's Research Institute

Results (where available)

View Results

Links

Published on BioPortfolio: 2016-01-12T12:38:23-0500

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